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  • Exam Name: Advanced Analytics Specialist Exam for Data Scientists
  • Last Update: Jan 13, 2025
  • Questions and Answers: 66
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E20-065 Practice Exam Questions with Answers Advanced Analytics Specialist Exam for Data Scientists Certification

Question # 6

What is NOT a category of a NoSQL data store?

A.

Columnar

B.

Document

C.

Key/Value

D.

Flat File

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Question # 7

What are the major components of the YARN architecture?

A.

ResourceManager and NodeManager

B.

Task Tracker and NameNode

C.

HDFS, Tez, and Spark

D.

Avro, ZooKeeper, and HDFS

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Question # 8

How can you improve processing performance in HIVE?

A.

Partition tables

B.

Run the SET hive.exec.parallel = false command

C.

Ensure highly normalized tables and use joins

D.

Minimize bucketing

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Question # 9

Assuming the node index starts at 1, what is the out-degree of node 3 in the adjacency matrix shown?

Refer to the exhibit.

E20-065 question answer

A.

0

B.

1

C.

2

D.

3

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Question # 10

What best describes tokenization?

A.

Adding lexical relations to the raw text

B.

Converting text into the list of terms

C.

Converting text into a list of unique terms

D.

Reducing variant forms of tokens to their base forms

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Question # 11

Which representation is most suitable for a small and highly connected network?

A.

Edge list

B.

Adjacency matrix

C.

Eigenvector centrality

D.

Adjacency list

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Question # 12

Given an input vector of features, a Random Forests model performs a classification task and ends in a tie.

How does the model handle this outcome?

A.

The model will be rebuilt

B.

A winner is chosen at random

C.

The tree that caused the tie is discarded

D.

One more tree is added to the forest

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Question # 13

What elements are needed to determine the time complexity of finding all the cliques of size k in social network analysis?

A.

Eigenvector centrality and betwenness

B.

Clique size and total number of nodes in the network

C.

Number of edges in the network and centrality measure of the cliques

D.

Clique size and betweenness centrality

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Question # 14

What are key characteristics of regular lattices?

A.

Low clustering coefficients, high network diameters

B.

High clustering coefficients, small network diameters

C.

Low clustering coefficients; small network diameters

D.

High clustering coefficients; high network diameters

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Question # 15

In which step in the visualization lifecycle would you determine how the raw data is stored?

A.

Visualization Planning

B.

Data Preparation

C.

Visualization Building

D.

Discovery

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Question # 16

What is an ideal use case for HDFS?

A.

Storing files that are updated frequently

B.

Storing files that are written once and read many times

C.

Storing results between Map steps and Reduce steps

D.

Storing application files in memory

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Question # 17

Which metric would be most helpful in identifying a node that may cause network disruption if the node were removed?

A.

Degree

B.

Closeness

C.

Betweenness

D.

PageRank

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Question # 18

What is a random subspace of features, as used by Random Forests?

A.

A random subset of features that are chosen at each split in the decision tree

B.

Filtration of data that does not meet a pre-defined weighting thrsehold

C.

The creation of out-of-bag (OOB) data that is used to select features

D.

Removal of highly correlated variables to randomize the features

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Question # 19

A data engineer is asked to process several large datasets using MapReduce. Upon initial inspection the engineer realizes that there are complex interdependencies between the datasets.

Why is this a problem?

A.

MapReduce works best on unstructured data

B.

There is no problem; MapReduce accommodates all the data

C.

MapReduce can only parse one file at a time.

D.

MapReduce is not ideal when the processing of one dataset depends on another.

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